Predicting-critical-Temperature-Tc-of-super-conductor

About

A superconductor is a substance that conducts electricity without resistance when it becomes colder than a critical temperature. The intention of this Notebook is do an Expolatory Data Analysis on the given data and:

1)Find the factors the affects Tc.

2)Visualizing the given data in 2D in space using PCA.

3)Develope and compare Various models for predicting Tc.

Objective

Creat a good model for Predicting Critical Temperature(Tc) of Superconductor

Technical Aspect

This project is divided into two part:

1. Visualize the data by using Matplotlib and Seaborn.

2. Training a Machine Learning model using Scikit-learn.

3. Training the data by using Scikit-learn

•)For predicting the Critical Temperature(Tc) i used :

1. Linear Regression.
2. Decision Tree Regression
3. Random Forest Regression
4. Bagging Regression
5. Random Forest + Bagging

Result

From these models Random Forest Regression model gives highest score when compared to other models (0.92)

Tools Used

1. Python
2. Pandas
3. Scikit-learn
4. Matplotlib
5. Numpy
6. Seaborn
7. Jupyter Notebook

Technologies Used

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